I just started using Tensorflow and Keras not long along ago, and I really like the field of deep learning. Right now I am doing it as more of a hobby than anything, and I recently learned about the concepts of transfer learning and fine-tuning. I tried to apply them to a dataset of microscopic images using the tutorial here: https://www.tensorflow.org/tutorials/images/transfer_learning.
I am using ResNet50 with the ImageNet weights, but am far from getting good results. I think it might be because of the learning rate OR because of the activation function in my last layer OR because of the fact that I use the Adam optimizer and not SGD.
Would someone be willing to look into my code to see what’s wrong? I have uploaded it as a pdf here: https://www.mediafire.com/file/vteka9uje8lthnb/NNonNema.pdf/file
Please note that the document is long because I printed model.summary() at some point, which showed all the layers!